A hybrid machine learning and ied-based fault detection scheme for microgrids by Hamid Radmanesh, Abolfazl Hadadi

“…Additionally, the proposed algorithm achieves higher fault detection speed and improved computational efficiency compared to other methods. …”
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Applying a Convolutional Vision Transformer for Emotion Recognition in Children with Autism: Fusion of Facial Expressions and Speech Features by Yonggu Wang, Kailin Pan, Yifan Shao, Jiarong Ma, Xiaojuan Li

“…Emotion recognition and the detection of autism in children are prominent subjects in autism research. …”
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MobileNetV3: an efficient deep learning-based feature selection and classification technique for cardiovascular disease by B. Dhanalaxmi, B. Naveen Kumar, Yeligeti Raju, Rama Seshagiri Rao Channapragada

“…Next, use the EfficientNetV2 approach to extract the features from the data, and then use the Reptile Search Algorithm (RSA) to choose the most significant features from the collected features. …”
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K-Nearest Neighbors for Anomaly Detection and Predictive Maintenance in Water Pumping Systems by João Pablo Santos da Silva, André Laurindo Maitelli

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Surface Deformation and Straightness Detection of Electromagnetic Launcher Based on Laser Point Clouds by Kangwei Yan, Delin Zeng, Long Cheng, Sai Tan

“…First, the system composition and detection principles are introduced. Second, the impacts of the detection device’s attitude deflection are analyzed. …”
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DM-YOLO: improved YOLOv9 model for tomato leaf disease detection by Abudukelimu Abulizi, Junxiang Ye, Halidanmu Abudukelimu, Wenqiang Guo

“…Therefore, an improved tomato leaf disease detection method, DM-YOLO, based on the YOLOv9 algorithm, is proposed in this paper. …”
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A lightweight steel surface defect detection network based on YOLOv9 by Tianyi Zheng, Ling Yu, Yongbao Shi, Fanglin Niu

“…To address the issues of high computational cost and low detection accuracy in current steel defect detection models, we propose a YOLOv9-based steel defect detection algorithm, CCSS-YOLO. …”
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Automated Lightweight Model for Asthma Detection Using Respiratory and Cough Sound Signals by Shuting Xu, Ravinesh C. Deo, Oliver Faust, Prabal D. Barua, Jeffrey Soar, Rajendra Acharya

“…<b>Methods:</b> To build an automated, lightweight model for asthma detection, tested separately with respiratory and cough sounds to assess their suitability for detecting asthma and COPD, the proposed AI models integrate the following ML algorithms: RF, SVM, DT, NN, and KNN, with an overall aim to demonstrate the efficacy of the proposed method for future clinical use. …”
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Triplet Spatial Reconstruction Attention-Based Lightweight Ship Component Detection for Intelligent Manufacturing by Bocheng Feng, Zhenqiu Yao, Chuanpu Feng

“…To address the requirements of shipbuilding industrial applications, a Triplet Spatial Reconstruction Attention (TSA) mechanism that combines threshold-based feature separation with triplet parallel processing is proposed, and a lightweight You Only Look Once Ship (YOLO-Ship) detection network is constructed. …”
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Binary Large Object-Based Approach for QR Code Detection in Uncontrolled Environments by Omar Lopez-Rincon, Oleg Starostenko, Vicente Alarcon-Aquino, Juan C. Galan-Hernandez

“…The proposal consists in recognizing geometrical features of QR code using a binary large object- (BLOB-) based algorithm with subsequent iterative filtering QR symbol position detection patterns that do not require complex processing and training of classifiers frequently used for these purposes. …”
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Multimodal image fusion for ich detection and classification using parallel Dl models by Sri Sangepu Nagaraju, S. Prince Mary, V. Pavani Chandra, Nandam Gayatri

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Fish Disease Detection Using Image Based Machine Learning Technique in Aquaculture by Md Shoaib Ahmed, Tanjim Taharat Aurpa, Md. Abul Kalam Azad

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G-RCenterNet: Reinforced CenterNet for Robotic Arm Grasp Detection by Jimeng Bai, Guohua Cao

“…First, a channel and spatial attention mechanism is introduced to improve the network’s capability to extract target features, significantly enhancing grasp detection performance in complex backgrounds. …”
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DeepGuard: Enhancing Violence Detection in Smart Cities Through Deep Learning by Md. Al-Mamun Provath, Musfequa Rahman, Kaushik Deb, Pranab Kumar Dhar, Tetsuya Shimamura

“…In addition, a custom keyframe extraction algorithm was designed, using temporal and pixel-level features to improve stability and accuracy. …”
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Detection of Indoor Building Lighting Fixtures in Point Cloud Data using SDBSCAN by Humairah Mansor, Shazmin Aniza Abdul Shukor, Razak Wong Chen Keng, Nurul Syahirah Khalid

“…It is expected that the developed algorithm can be used to detect and classify fixtures from any 3D point cloud data representing buildings.…”
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A New, Robust, Adaptive, Versatile, and Scalable Abandoned Object Detection Approach Based on DeepSORT Dynamic Prompts, and Customized LLM for Smart Video Surveillance by Merve Yilmazer, Mehmet Karakose

“…Then, human and object classes were detected using the weights of the YOLOv8l model, which has a fast and effective object detection feature. …”
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Vehicle detection in drone aerial views based on lightweight OSD-YOLOv10 by Yang Zhang, Xiaobing Chen, Su Sun, Hongfeng You, Yuanyuan Wang, Jianchu Lin, Jiacheng Wang

“…Abstract To address the challenges of low performance in vehicle image detection from UAV aerial imagery, difficulties in small target feature extraction, and the large parameter size of existing models, we propose the OSD-YOLOv10 algorithm, an enhanced version based on YOLOv10n. …”
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Remote Sensing Image Detection Method Combining Dynamic Convolution and Attention Mechanism by Yunfei Zhang, Ming Chen, Cong Chen

“…Traditional CNN downsampling often leads to the loss of small object details and missed detections. This paper proposes an improved YOLOv8 algorithm, incorporating adaptive feature extraction and multi-scale fusion modules to enhance feature representation, effectively capturing the details of small objects. …”
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Robust SAR Change Detection Using Hierarchical Clustering With Adaptive Parameter Tuning by Ahidjo Abdoulaye, Alejandro C. Frery, Mingyang Ma, Shaohui Mei

“…Change detection in synthetic aperture radar imagery is challenging due to noise, complex nonlinear features, and variations in underlying data distributions. …”
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Multimodal ultrasound deep learning to detect fibrosis in early chronic kidney disease by Xiachuan Qin, Xiaoling Liu, Linlin Xia, Qi Luo, Chaoxue Zhang

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